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ABSTRACT: Post-Translational Modifications (PTMs) play most important roles in the accomplishment of biological processes and molecular functions. It is challenging to identify two PTMs for a tandem mass spectrum. In this paper, we proposed a new algorithm to detect two PTMs with unknown types. First, we constructed a Pair of Peak Set (PPS) which is composed of pairs of peaks that have the highest sum of intensities. Second, we revealed the relationship between PPS and the whole experimental spectrum. Third, a series of logic conditions was proposed to detect PTMs from a MS/MS spectrum. Finally, we used a scoring function to rank the candidate hits. We applied the method to a large MS/MS data set and the experimental results demonstrated that the proposed method achieved better performance of identifying any types of PTMs in a blind mode than current existing methods.
International Journal of Computational Biology and Drug Design 01/2012; 5(3-4):314-24.
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ABSTRACT: Protein domains are structural and fundamental functional units of proteins. The information of protein domain boundaries is helpful in understanding the evolution, structures and functions of proteins, and also plays an important role in protein classification. In this paper, we propose a support vector regression-based method to address the problem of protein domain boundary identification based on novel input profiles extracted from AAindex database. As a result, our method achieves an average sensitivity of approximately 36.5% and an average specificity of approximately 81% for multi-domain protein chains, which is overall better than the performance of published approaches to identify domain boundary. As our method used sequence information alone, our method is simpler and faster.
Amino Acids 02/2010; 39(3):713-26. · 3.25 Impact Factor
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ABSTRACT: A contact map is a key factor representing a specific protein structure. To simplify the protein contact map prediction, we predict the inter-residue contact clusters centred at the groups of their surrounding inter-residue contacts. In this paper, we adopt a Support Vector Machine (SVM)-based approach to predict the inter-residue contact cluster centres. The input of the SVM predictor includes sequence profile, evolutionary rate and predicted secondary structure. The SVM predictor is based on hydrophobic cores that may be considered as locations of the inter-residue contact clusters. About 35% of clustering centres of inter-residue contacts can be predicted accurately.
International Journal of Data Mining and Bioinformatics 01/2010; 4(6):722-34. · 0.43 Impact Factor
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ABSTRACT: Alcohol abuse and alcoholism are serious and costly problem in USA. Thus, the development of anti-alcoholism agents could be very significant. The understanding of the neurochemical basis underlying the addictive properties of drugs of abuse is imperative for the development of new pharmacological means to reverse the addictive state, prevent relapse or to reduce the intake of addictive compounds. The nicotinic acetylcholine receptors (nAChRs) are important therapeutic targets for various diseases. Recent studies have revealed that the alpha3beta2, alpha3beta3, and alpha6 subunits of nAChR protein family might be pharmacological targets for developing new drugs in the treatment of alcoholism. We have performed computational homology modeling of the alpha3beta2, alpha3beta3, and alpha6 subunits of human nACHRs based upon the recently determined crystal structure of the extracellular domain (ECD) of the mouse nAChR alpha1 subunit complexed with alpha-bungarotoxin at 1.94 A resolution. For comparison, we also built the ECD models of alpha4beta2, and alpha7 subunits of human nACHRs which are neurochemical targets for cessation of smoking. The three-dimensional (3D) models of the ECD of the monomer, and pentamer of these human nAChR were constructed. The docking of the agonist in the ligand-binding pocket of the human nAChR dimers was also performed. Since the nAChR ligand-binding site is a useful target for mutagenesis studies and the rational design of drugs against various diseases, these models provide useful information for future investigation.
Interdisciplinary Sciences Computational Life Sciences 12/2009; 1(4):254-62.
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ABSTRACT: Protein fold classification is a key step to predicting protein tertiary structures. This paper proposes a novel approach based on genetic algorithms and feature selection to classifying protein folds. Our dataset is divided into a training dataset and a test dataset. Each individual for the genetic algorithms represents a selection function of the feature vectors of the training dataset. A support vector machine is applied to each individual to evaluate the fitness value (fold classification rate) of each individual. The aim of the genetic algorithms is to search for the best individual that produces the highest fold classification rate. The best individual is then applied to the feature vectors of the test dataset and a support vector machine is built to classify protein folds based on selected features. Our experimental results on Ding and Dubchak's benchmark dataset of 27-class folds show that our approach achieves an accuracy of 71.28%, which outperforms current state-of-the-art protein fold predictors.
Journal of Bioinformatics and Computational Biology 10/2009; 7(5):773-88.
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ABSTRACT: In recent years, virtual database screening using high-throughput docking (HTD) has emerged as a very important tool and a well-established method for finding new lead compounds in the drug discovery process. With the advent of powerful personal computers (PCs), it is now plausible to perform HTD investigations on these inexpensive PCs. To make HTD more accessible to a broad community, we present here WinDock, an integrated application designed to help researchers perform structure-based drug discovery tasks under a uniform, user friendly graphical interface for Windows-based PCs. WinDock combines existing small molecule searchable three-dimensional (3D) libraries, homology modeling tools, and ligand-protein docking programs in a semi-automatic, interactive manner, which guides the user through the use of each integrated software component. WinDock is coded in C++.
Journal of Computational Chemistry 12/2007; 28(14):2347-51. · 4.58 Impact Factor
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Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on; 08/2007
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ABSTRACT: The emergence of drug-resistant HIV-1 strains presents a challenge for the design of new drugs. Targeting host cell factors involved in the regulation of HIV-1 replication might be one way to overcome the resistance of HIV-1 to anti-viral agents. Our recent studies identified protein phosphatase-1 (PP1) as an important regulator of HIV-1 transcription. Transcription of HIV-1 genes is activated by HIV-1 Tat protein that induces phosphorylation of the C-terminal domain of RNA polymerase-II by CDK9/cyclin T1. We have shown that HIV-1 Tat binds PP1 in vitro; targets PP1 to the nucleus; and that Tat interaction with PP1 is important for HIV-1 transcription. In this review, we discuss two potential targets of PP1 in Tat-induced HIV-1 transcription: the C-terminal domain of RNA polymerase-II and CDK9. We also present a computer model of Tat-PP1 complex that might be useful for future drug design in anti-HIV-1 therapeutics.
Current HIV research 02/2007; 5(1):3-9. · 1.98 Impact Factor
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ABSTRACT: Transcription of HIV-1 genes is activated by HIV-1 Tat protein, which induces phosphorylation of RNA polymerase II (RNAPII) C-terminal domain (CTD) by CDK9/cyclin T1. Earlier we showed that CDK2/cyclin E phosphorylates HIV-1 Tat in vitro. We also showed that CDK2 induces HIV-1 transcription in vitro and that inhibition of CDK2 expression by RNA interference inhibits HIV-1 transcription and viral replication in cultured cells. In the present study, we analyzed whether Tat is phosphorylated in cultured cells by CDK2 and whether Tat phosphorylation has a regulatory effect on HIV-1 transcription.
We analyzed HIV-1 Tat phosphorylation by CDK2 in vitro and identified Ser16 and Ser46 residues of Tat as potential phosphorylation sites. Tat was phosphorylated in HeLa cells infected with Tat-expressing adenovirus and metabolically labeled with 32P. CDK2-specific siRNA reduced the amount and the activity of cellular CDK2 and significantly decreased phosphorylation of Tat. Tat co-migrated with CDK2 on glycerol gradient and co-immunoprecipitated with CDK2 from the cellular extracts. Tat was phosphorylated on serine residues in vivo, and mutations of Ser16 and Ser46 residues of Tat reduced Tat phosphorylation in vivo. Mutation of Ser16 and Ser46 residues of Tat reduced HIV-1 transcription in transiently transfected cells. The mutations of Tat also inhibited HIV-1 viral replication and Tat phosphorylation in the context of the integrated HIV-1 provirus. Analysis of physiological importance of the S16QP(K/R)19 and S46YGR49 sequences of Tat showed that Ser16 and Ser46 and R49 residues are highly conserved whereas mutation of the (K/R)19 residue correlated with non-progression of HIV-1 disease.
Our results indicate for the first time that Tat is phosphorylated in vivo; Tat phosphorylation is likely to be mediated by CDK2; and phosphorylation of Tat is important for HIV-1 transcription.
Retrovirology 02/2006; 3:78. · 6.47 Impact Factor
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ABSTRACT: Transcription of human immunodeficiency virus (HIV)-1 genes is activated by HIV-1 Tat protein, which induces phosphorylation of the C-terminal domain of RNA polymerase-II by CDK9/cyclin T1. We previously showed that Tat-induced HIV-1 transcription is regulated by protein phosphatase-1 (PP1). In the present study we demonstrate that Tat interacts with PP1 and that disruption of this interaction prevents induction of HIV-1 transcription. We show that PP1 interacts with Tat in part through the binding of Val36 and Phe38 of Tat to PP1 and that Tat is involved in the nuclear and subnuclear targeting of PP1. The PP1 binding mutant Tat-V36A/F38A displayed a decreased affinity for PP1 and was a poor activator of HIV-1 transcription. Surprisingly, Tat-Q35R mutant that had a higher affinity for PP1 was also a poor activator of HIV-1 transcription, because strong PP1 binding competed out binding of Tat to CDK9/cyclin T1. Our results suggest that Tat might function as a nuclear regulator of PP1 and that interaction of Tat with PP1 is critical for activation of HIV-1 transcription by Tat.
Journal of Biological Chemistry 11/2005; 280(43):36364-71. · 4.77 Impact Factor
